Helmholtz Imaging Projects

Visual, Helmholtz Imaging Project POINTR, topic: Mapping Boreal Forest Change Using 3D Radar and Point Cloud Data

Image: Stefan Kruse

Published on 11.06.2025

POINTR

Global warming is reshaping northern boreal forests. This project maps forest structure and ecosystem services using high-resolution radar satellite monitoring combined with 3D imaging data.

This image shows simulation results comparing MWF mapping with single inversions of "T2-decay" data, "T2*-decay" data, and with joint inversion of both. The joint inversion is significantly closer to ground truth, as the second row shows.

Published on 02.06.2025

JIMM2

Changes in brain myelin are linked to many neurological diseases. This project aims to improve myelin water imaging, enabling more accurate and accessible diagnostics.

Image: FOMIA

Published on 27.05.2025

FOMIA

This project will develop a foundation model trained on a large and diverse dataset of microscopy images to facilitate the adaptation of artificial intelligence methods to biological image analysis.

Visual for Helmholtz Imaging Project PlastoView

Image: PlastoView

Published on 27.05.2025

Water quality is essential for ecosystems and human health, yet it’s increasingly threatened by microplastics. This project develops image-based methods for detecting both plankton and microplastics using a new low-cost, mobile system.

Published on 19.05.2025

cryoFocal

This project explores how defocused images recorded with an electron microscope can be used to reconstruct the 3D structure of molecules inside cells. This method aims to enable faster and more cost-effective structural analysis of molecules to accelerate understanding of their functions and to design drugs against them.

Published on 30.10.2024

Fast-EMI

A novel imaging approach combining electron microscopy and deep learning has been established. This method enables adaptive tracking of atomic defects, accelerating material development for the energy transition.

Published on 07.10.2024

BrainShapes

The project explores the 3D structure of the human brain by creating a digital ‘map’ of the brain and examining its unique genetic properties, potentially linking genetic variations to brain disorders.

Published on 19.08.2024

CLARITY

Dose-escalated radiotherapy of lung cancers requires precise monitoring of lesions and nearby organs at risk. Current methods are able to track ultra-central lesions but neglect their deforming vicinity, risking unacceptable toxicity to aortico-pulmonary structures. AI-based anomaly detection and generative AI models can address both requirements in real-time.

Published on 14.08.2024

3DforestSIF

3DforestSIF seeks to correct airborne solar-induced fluorescence (SIF) data from forests for canopy structural and illumination effects, providing valuable insights for the early detection of forest stress.

Image: X-BRAIN

Published on 14.08.2024

X-BRAIN

This project aims to develop AI methods that support the integration of multimodal imaging data into human brain atlases, thereby advancing the analysis of brain structure in both health and disease.

Image: Aaron Christian Banze

Published on 09.08.2024

HYPER-AMPLIFAI

The project aims to make advanced AI models accessible for Hyperspectral Earth Observation, reducing computational demands, and improving environmental assessments through user-friendly interfaces.

Image: Jonas Baumann, HIPS

Published on 28.08.2023

ImageTox

ImageTox wants to establish an automated image-based system to assess zebrafish larval development. This will allow for a fast and unbiased evaluation of pathophysiological events during toxicological studies. To achieve this, the imaging process has to be optimized and a reliable model for sequence recognition based on deep learning has to be developed.

Published on 28.08.2023

HighLine

MR images of roots and vessels are very similar: both display thin, line-like objects. The aim of the project is to increase image quality of both kind of MR data by exploiting their similarity. HighLine aims at obtaining high quality images in reduced scan time to lower patient burden and increase patient and plant throughput by adapting state-of-the-art 3D image enhancement methods, and developing new deep-learning based methods.

Image: Johannes Seiffarth, FZ Jülich

Published on 28.08.2023

EMSIG

Microfluidic live-cell imaging (MLCI) unlocks spatio-temporal insights into population heterogeneity emerging from a single cell. EMSIG brings smart live-event detection capabilities to MLCI to facilitate the adaptive optimization of biological event resolution and autonomously counteracting deteriorating image qualities.

Published on 28.08.2023

DIPLO

This project will develop a user-friendly software platform to analyze plankton images independent of the instrument with which images were collected. This will help to compare data and create a common database, which is a critical step towards an image-based ecosystem component of a “Digital Twin Ocean”.